Efficient user interaction with polygonal meshes for medical image segmentation

ABSTRACT

An apparatus for delineating a structure of interest includes: a plane selection interface for selecting a contouring plane of selectable orientation in a three-dimensional image or map; a contouring interface for defining a contour in the selected contour plane; and a mesh constructor configured to construct a three-dimensional polygonal mesh delineating the structure of interest in the three-dimensional image or map. The mesh constructor positions constrained vertices on or near a plurality of non-coplanar delineation contours defined using the contouring interface.

This application is a continuation of U.S. application Ser. No.12/374,108 filed Jan. 16, 2009 and since issued as U.S. Pat. No.8,660,325 on Feb. 25, 2014, which is a National Stage of InternationalApplication No. PCT/US2007/72646 filed Jul. 2, 2007 which claims thebenefit of U.S. Provisional Application No. 60/807,531 filed Jul. 17,2006. U.S. application Ser. No. 12/374,108 filed Jan. 16, 2009 isincorporated herein by reference in its entirety.

The following relates to the graphical arts. It is described withexample reference to medical applications in which structures of amedical image are to be defined preparatory to radiation therapyplanning or other medical procedure planning. However, the followingrelates more generally to defining structures in substantially any typeof three-dimensional image, three-dimensional map, or the like, and toapplications other than radiation therapy planning, such asvisualization or other post-acquisition image processing, sculpting outfeatures in a three-dimensional image to enable viewing or otherpost-acquisition image processing of hidden anatomical structures,estimating absorption characteristics of structures for use insubsequent SPECT or PET imaging data reconstruction, or so forth.

In oncological radiation therapy (sometimes called radiotherapy),ionizing radiation is applied to kill or retard growth of canceroustumors or growths. Problematically, however, the radiation alsoadversely affects surrounding healthy tissue.

In intensity modulated radiation therapy, one or more radiation beamsare applied to a patient, with a configuration biased toward irradiatingthe cancerous tumor or growth and biased away from irradiatingbiologically critical healthy tissue. In fixed-beam approaches, aplurality of crossing beams are applied simultaneously such that thebeams overlap within the patient. The spatial beam intensity profile ofeach beam is controlled, for example by multi-leaf collimators. Bysuitable selection of the spatial beam intensity profiles, and takinginto account the crossing of beamlets from different beams within thepatient, a desired three-dimensional profile of radiation intensity inthe patient can be achieved. In tomographic approaches, at least onebeam is rotated or stepped around the patient, with the spatial beamintensity profile modified during the rotation or stepping such that thetime-integrated radiation dosage matches the desired three-dimensionalprofile within the patient.

Effective application of intensity modulated radiation therapy reliesupon having a priori knowledge of the shape and size of the canceroustumor or growth, as well as having a priori knowledge of the shape andsize of neighboring critical tissues whose radiation exposure should beminimized or kept below a threshold value. In a common approach, this apriori knowledge is obtained using a medical imaging technique such astransmission computed tomography (CT), single-photon emission computedtomography (SPECT), positron emission tomography (PET), magneticresonance imaging (MRI), or the like. For radiotherapy planning, CT hasthe advantage of providing anatomical information and tissue radiationabsorption characteristics. The latter is typically taken into accountduring planning of the radiation therapy session, to more accuratelycompute the three-dimensional radiation profile. Some example techniquesfor planning of an intensity modulated radiation therapy session basedon CT planning images are described, for example, in McNutt et al., U.S.Pat. No. 6,735,277.

During radiotherapy planning, the CT planning image is analyzed toidentify the cancerous tumor or growth as well as critical structureswhose radiation exposure is to be limited. One approach is to model astructure of interest using a surface mesh, and to use an automated meshdeformation technique to deform the mesh to align with the surface ofthe structure of interest. Typically, the surface is defined byintensity gradients in the CT image.

Contouring critical and target structures is a sensitive,labor-intensive, and time-consuming process. For example, contouring ofthe head and neck in a three-dimensional image or map preparatory toradiation therapy can take several hours. Automated segmentationalgorithms have been developed to improve the process, and have beenapplied to delineation of at-risk organs in various treatment sites suchas the prostate, liver, breast, lungs, and brain. In one approach, apolygonal mesh with triangular elements is deformed under elasticity andimage feature constraints to match an object's surface in an image.Prior knowledge is encoded in such an algorithm by providing averagemeshes for initialization, and encoding characteristics regarding greyvalue range, gradient strength etc. on the surface into each model.

Existing automated mesh deformation techniques have certain limitations,however. For example, if the surface of the structure of interest is notwell-defined, the fitted mesh may be inaccurate or uncertain. Somestructures, such as the lymph nodes in the neck, have sufficiently poorimage contrast to effectively preclude the use of automated segmentationon these features. In other cases, most of the structure may havesufficient image contrast to enable automated segmentation, but certainportions of the imaged structure may exhibit poor image contrast,resulting in failure or substantial errors in the automated segmentationin those poor-contrast areas.

It is known to supplement image features with manually drawn contours.For example, Pekar et al., Int'l. Application Publ. No. WO 2004/111937A1, discloses an approach for applying deformation techniques in regionsof a three-dimensional dataset made up of two-dimensional slices. Wherethe slices provide insufficient feature information such that theautomated segmentation fails, the user may manually define attractors inthe problematic slices. The manually drawn attractors are then usedduring subsequent automated mesh deformation to guide the automatedsegmentation in the problematic axial slices.

It is also known to allow for manual interaction with the mesh, forexample by providing the user with a graphical user interface andclick-and-drag pointer instrument (e.g., mouse) operational interfacing.For example, Kaus et al., Int'l Application Publ. No. WO 2004/053792 A1,discloses a method of segmenting a three-dimensional structure usingautomated deformable mesh optimization, with initial and/or subsequentmanual displacement of mesh vertices or nodes in selected regions of theautomated mesh fit, optionally followed by further optimization of themesh.

Such existing techniques are not entirely satisfactory where largeportions of the structure of interest are poorly defined in thethree-dimensional image. Applying the approach of Pekar to such casescalls for drawing attractors in many slices of the three-dimensionaldataset that intersect the extended portion or portions of the structureof interest having poor contrast. This is a time-consuming and tediousprocess. Moreover, it may be difficult for the user to visually identifythe structure of interest in the slice image so as to draw in theattractors. Applying the approach of Kaus to such cases calls forinitial and/or corrective manual adjustment of many vertices or nodes ofthe mesh, which is again a time-consuming and tedious process.

In the present disclosure, method and apparatus embodiments aredisclosed.

In an example method of delineating a structure of interest in athree-dimensional image or map, at least two contours delineating thestructure of interest are defined. The at least two contours lie in atleast two different contouring planes that are different andnon-parallel respective to each other. A three-dimensional polygonalmesh is fitted while respecting the defined contours as constraints onvertices of the polygonal mesh.

In an example apparatus, a plane selection interface is provided forselecting a contouring plane of selectable orientation in athree-dimensional image or map. A contouring interface is provided fordefining a contour in the selected contour plane. A mesh constructor isconfigured to construct a three-dimensional polygonal mesh delineating astructure of interest in the three-dimensional image or map. The meshconstructor positions constrained vertices on or near a plurality ofnon-coplanar delineation contours defined using the contouringinterface.

In an example apparatus which is operative in conjunction with anadaptive treatment process, a segmenting processor is configured todelineate a structure. The segmenting processor includes: (i) acontouring interface configured to define structure-delineating contoursin at least two different, non-parallel contouring planes; and (ii) amesh constructor for constructing a mesh using a mesh deformationprocess constrained at least by the defined structure-delineatingcontours. A planning processor is configured to identify parameters foradaptive treatment of a subject based on delineation via the segmentingprocessor of at least one structure of interest in a three-dimensionalimage or map of the subject.

One advantage resides in facilitating rapid and accurate segmentation ordelineation of structures of interest.

Another advantage resides in efficient integration of manual andautomated inputs to a mesh deformation process.

Another advantage resides in more rapid and accurate planning ofadaptive treatment processes such as intensity modulated radiationtherapy.

Still further advantages of the present invention will be appreciated tothose of ordinary skill in the art upon reading and understand thefollowing detailed description.

The invention may take form in various components and arrangements ofcomponents, and in various steps and arrangements of steps. The drawingsare only for purposes of illustrating the preferred embodiments and arenot to be construed as limiting the invention.

FIG. 1 diagrammatically shows an example intensity modulated radiationtherapy system including CT imaging based planning.

FIG. 2 diagrammatically shows principal components of the contouringprocessor 44 of FIG. 1 with principal data structures and principal dataflow diagrammatically indicated.

FIG. 3 diagrammatically shows two example contouring planes selected tointerest a spine S: a coronal contouring plane P_(cor) and an obliquecontouring plane P_(obl) that is oriented orthogonal to the coronalcontouring plane P_(cor).

FIG. 4 diagrammatically shows contours C_(cor) delineating the spine Sdefined in the coronal contouring plane P_(cor).

FIG. 5 diagrammatically shows contours C_(obl) delineating the spine Sdefined in the oblique contouring plane P_(obl).

FIG. 6 diagrammatically shows a portion of a polygonal mesh M_(S) havingtriangular elements deformed to match the coronal and oblique contoursC_(cor), C_(obl) of FIGS. 4 and 5.

FIG. 7 diagrammatically shows principal components of thethree-dimensional mesh optimizer 76 of FIGS. 1 and 2 with principal datastructures and data flow diagrammatically indicated.

With reference to FIG. 1, a radiation therapy system 10 includes acomputed tomography (CT) scanner 12 for obtaining CT planning images foruse in planning an intensity modulated radiation therapy treatmentsession. The CT scanner 12 includes an x-ray source 14 mounted on arotating gantry 16 so as to revolve around an examination region 18, acouch or other support 20 for positioning a subject in the examinationregion 18, and an x-ray detector array 22 arranged on the rotatinggantry 16 opposite the x-ray source 14 to detect x-rays after they havepassed through the subject in the examination region 18. The CT scanner12 is used to acquire projection data, such as projection data for aplurality of axial image slices (e.g., a multi-slice CT scanner), or ahelical three-dimensional projection dataset (e.g., a helical CTscanner), or so forth. The projection data are stored in an imaging datamemory 24, and are reconstructed by a reconstruction processor 26 usinga suitable algorithm such as filtered backprojection to generate aplurality of stacked axial image slices or other image data structuresdefining a three-dimensional image or map of the subject that is storedin a planning images memory 28. The CT scanner 12 is operated by a CTcontroller 30 that sets or controls scan parameters such as gantryrotation rate, helical pitch (in the case of a helical scan), axial scandistance, and so forth. A user interface 32 including at least one inputdevice, such as an illustrated keyboard 34, a pointing device such as anillustrated mouse 36, or so forth, and at least one output device, suchas the illustrated display 38, is provided to enable a user to interfacewith the CT controller 30 to operate the CT scanner 12 to acquireplanning images for planning an intensity modulated radiation therapysession.

The described CT scanner 12 is an illustrative example of a planningimage or map acquisition system. In other embodiments, planning imagesmay be acquired using a single photon emission computed tomography(SPECT) system, a positron emission tomography (PET) scanner, a magneticresonance (MR) scanner, or so forth. Moreover, the techniques disclosedherein for delineating structures of interest in a planning image areapplicable to other adaptive treatment processes besides intensitymodulated radiation therapy. For example, the structure-delineatingtechniques disclosed herein are applicable to planning for surgicaltreatment such as stent implantation. Here, the structure of the stentis advantageously determined by non-invasive imaging and vesseldelineation in accordance with techniques disclosed herein, so that acustomized stent can be manufactured and available at the time of thestent implantation procedure. The choice of planning image or mapacquisition system may be based on the type of adaptive treatmentprocess being planned. For example, in the case of stent implantationplanning, MR imaging employing a suitable intravenous magnetic contrastagent is suitable.

Still further, the structure-delineating techniques disclosed hereinhave other applications beyond planning of adaptive treatment processes.For example, the structure-delineating techniques disclosed herein maybe used in visualization or other post-acquisition image processing. Inone example application, the structure-delineating techniques disclosedherein are used to delineate organs that are then sculpted out of athree-dimensional image to enable viewing or other post-acquisitionimage processing of hidden anatomical structures. As yet another exampleapplication, the structure delineating techniques disclosed herein canbe used to estimate absorption characteristics of structures for use insubsequent SPECT or PET imaging data reconstruction.

Returning to the example application of intensity modulated radiationtherapy illustrated in FIG. 1, the planning image or map acquisitionsystem 12 is separate from an intensity modulated radiation therapysystem to be described. Preferably, fiducial markers are attached to thesubject prior to acquiring the planning images, and these markers remainin place until the subsequent radiotherapy session to provide spatialregistration between the planning image or map and the radiotherapydelivery. Other methods for spatial registering between planning imageor map acquisition system and the radiotherapy system are alsocontemplated, such as using intrinsic anatomical markers such asdistinctive bone structures. Furthermore, it is also contemplated tointegrate the planning images or mapping acquisition system with theradiotherapy apparatus so that a common coordinate system is used forboth planning images acquisition and radiation therapy.

With continuing reference to FIG. 1, a density profiling processor 40optionally computes a density profile map of the subject. Such a densityprofile is typically used to estimate absorption of therapeuticradiation during radiation therapy. Advantageously, if the planningimaging technique is transmission CT as illustrated, then the absorptionof therapeutic radiation is typically relatively accurately estimatedbased on absorption of x-rays from the x-ray tube 12 as indicated in theCT planning images. In some embodiments, the structure-delineatingtechniques disclosed herein are used to delineate structures for whichdensity profiles or values are computed. For example, bones may bedelineated and assigned a bone density by the density profilingprocessor 40, and similarly other tissues such as cardiac tissue, lungtissue, muscle tissue, and so forth are delineated and assigned suitabletissue density values by the density profiling processor 40. In thislatter approach, the imaging technique can be radiation based (e.g., CT)or non-radiation based (e.g., MR), since the density values are assignedbased on anatomical information rather than based on measured x-rayabsorption.

A contouring processor 44 delineates structures of interest. In the caseof intensity modulated radiation therapy, structures of interest mayinclude, for example, the target cancerous tumor or growth, criticalstructures whose level of radiation exposure is to be limited, highlyabsorptive structures that may substantially interfere with delivery oftherapeutic radiation, and so forth. The structure delineationinformation may be used, for example, by the density profiling processor40 as already described, or by an inverse planning processor 50, or soforth.

One example approach for planning the intensity modulated radiationtherapy session based on acquired CT planning images is as follows. Theinverse planning processor 50 determines spatial beam intensity profilesfor therapeutic radiation beams that provide a desired three-dimensionalprofile of radiation intensity in the subject. The three-dimensionalprofile should provide sufficient radiation in the target structure(e.g., cancerous tumor or growth) to hopefully provide an anticipatedtherapeutic effect (as is understood in the art, variability amongstpatients dictates that the anticipated therapeutic effect mayunfortunately not occur in some patients, or may occur with varyingdegrees of effectiveness), while keeping radiation exposure of criticalstructures such as sensitive vital organs below selected thresholdexposure levels. For example, a radiation dosage of 80 Gy can betargeted for the area or areas to receive radiotherapy along with alimit of no more than 20% of this value (i.e., 16 Gy) in a criticalstructure that would likely be adversely affected by excessive radiationexposure. The planning also optionally incorporates system constraints,such as a maximum therapeutic radiation intensity level deliverable by atherapeutic beam source, spatial resolution limitations, or so forth. Inone planning approach, the therapeutic radiation beam is dividedmathematically into an array or other plurality of beamlets, and valuesare computed for the beamlets that provide a desired time-integratedthree-dimensional radiation profile in the subject. A conversionprocessor 52 converts the beamlet parameters to settings for multi-leafcollimators that control the (possibly time-varying) intensity profileof the therapeutic radiation beam or beams.

A radiation delivery apparatus controller 54 operates a radiationdelivery apparatus 56 in accordance with the planning information outputby the conversion processor 52 so as to deliver therapeutic radiation tothe subject in accordance with the plan determined from the CT planningimages. The illustrated example radiation delivery apparatus 56 is atomographic apparatus that has a stationary frame 58 with a rotating armor gantry 60 on which is mounted a therapeutic radiation source 62. Insome embodiments, the source 62 includes a linear electron accelerator(linac) which produces an accelerated electron beam that impinges upon atarget made of tungsten or another material to produce a therapeuticbeam of x-rays or gamma rays for photon radiotherapy. In otherembodiments, the therapeutic radiation source 62 produces other types ofradiation, such as proton beams, neutron beams, electron beams, or soforth.

The gantry 62 rotates so as to revolve the therapeutic radiation source60 around the patient who is positioned on a support 64. In oneapproach, the support 64 moves the subject linearly during the revolvingto effectuate a helical orbit of the radiation source about the subject.Ion another approach, a single slice or slab is irradiated with thesupport 64 stationary; if a larger area is to be irradiated, the support64 can be stepped to irradiate a succession of slices or slabs. Duringthe application of the therapeutic radiation, a multi-leaf collimator 66modulates the spatial intensity profile of the therapeutic radiationbeam in accordance with the plan output by the conversion processor 52so that the time-integrated radiation dosage delivered to the subjectaccords with the intended three-dimensional radiation profile.Typically, the multi-leaf collimator 66 includes an array ofindividually movable radiation-blocking paired leaves that togetherdefine a selectably sized and shaped radiation aperture.

In the illustrated tomographic radiation delivery apparatus 56, thesettings of the multi-leaf collimator 66 are typically varied during therevolving of the source 62 to produce the desired three-dimensionalprofile. In another approach, a plurality of radiation sources arespaced angularly apart around the subject, with the beams from theradiation sources crossing in the subject. Each beam has an associatedmulti-leaf collimator that imparts a spatial beam intensity profile inaccordance with the plan developed from the CT planning images such thatthe simultaneously applied beams crossing in the patient provide thedesired three-dimensional profile.

In order to register the position of the subject in the radiotherapysession (that is, the position of the subject on the support 64 of theradiation therapy delivery apparatus 56) with the position of thesubject in the previously acquired diagnostic images (that is, theposition of the subject on the support 20 of the CT system 12), fiducialmarkers are preferably used. In a suitable embodiment, detectors (notshown) receive low power x-rays produced by the radiation source 62 toeffectuate a low-resolution CT imaging which can be used to image thefiduciary markers which were placed on the subject prior to thediagnostic imaging. In another approach, a separate CT scanner (notshown) is integrated with the radiation therapy delivery apparatus toimage the fiducial markers.

Having described embodiments of an example intensity modulated radiationtherapy application with reference to FIG. 1, embodiments of thecontouring processor 44 are now described in greater detail. As shown inFIG. 1, the contouring processor 44 includes a contouring plane selector70, a contour selector 72, a three-dimensional mesh generator 74, and anoptional three-dimensional mesh optimizer 76.

With reference to FIG. 2, the contouring processor 44 operates on athree-dimensional image or map 80 generated by the CT scanner 12 and thereconstruction processor 26, without regard to any geometrical nature oraspects of the image or map acquisition. For example, thethree-dimensional image or map 80 may be acquired as a series of axialslices; however, the contouring processor 44 treats thethree-dimensional image or map 80 without regard to the axial slices.The contouring plane selector 70 operating in conjunction with the userinterface 32 allows a user to select two or more contouring planes 82.For example, the three-dimensional image or map 80, or a portionthereof, is suitably displayed on the display 38, and the user operatesa graphical pointer using the mouse 36, the keyboard 34, or anotherinput device to select the contouring planes 82. In general, the two ormore contouring planes 82 should include at least two different,non-parallel contouring planes to ensure adequate contouring of athree-dimensional structure of interest. In some embodiments, the atleast two different, non-parallel contouring planes include at least twodifferent, non-parallel planes selected from the group of planesconsisting of sagittal, coronal, and axial planes. In some embodiments,the at least two different, non-parallel contouring planes include atleast one oblique plane not belonging to the group of planes consistingof sagittal, coronal, and axial planes.

The contour selector 72 operating in conjunction with the user interface32 allows a user to select one or more delineation contours 84 in eachcontouring plane 82. For example, one of the contouring planes 82, or aportion thereof, is suitably displayed on the display 38, and the useroperates a graphical pointer using the mouse 36, the keyboard 34, oranother input device to draw one or more contours in the displayedcontouring plane 82. In one approach, the user designates points thatlie on the contour, and the contour is defined by the designated pointsand by connecting line segments that connect the designated points.Because the contouring planes 82 are user selected, it is possible forthe contouring plane to be oriented in an anatomically meaningful wayrespective to the structure of interest, which promotes easier and moreaccurate contouring. Moreover, the contours 84 are preferablynon-coplanar to ensure adequate contouring of the three-dimensionalstructure of interest. Typically, this condition is satisfied by drawingcontours in each of two or more different, non-parallel contouringplanes 82.

The three-dimensional mesh generator 74 constructs a three-dimensionalpolygonal mesh 90 delineating the structure of interest in thethree-dimensional image or map 80. The mesh 90 includes constrainedvertices each positioned on or near one or more of the non-coplanardelineation contours 84. In some embodiments, the mesh 90 is constructedby placing vertices of the mesh on the contours 84, without using adeformation process. In other embodiments, the mesh 90 is constructed bystarting with a default mesh configuration 92 that is placed close tothe structure of interest (for example, by placing it at a center of abounding box containing the contours 84, or at a center of gravity ofthe contours 84, or at another average or central position defined bythe delineating contours 84, or by placing the default meshconfiguration 92 at a center-of-gravity or other average or centralposition of the image of the structure of interest in thethree-dimensional image or map 80), and invoking the optionalthree-dimensional mesh optimizer 76 to deform the mesh to generate thethree-dimensional polygonal mesh 90 delineating the structure ofinterest in the three-dimensional image or map 80. Optionally, placementof the default mesh configuration 92 includes rotating, translating,scaling, or otherwise manipulating the default mesh configuration tomatch the contours 84 and/or the image of the structure of interest, forexample using an ICP-lie approach.

With continuing reference to FIG. 2 and with further reference to FIGS.3-6, operation of the contouring processor 44 is described withreference to an example delineation of a spinal column, such as might beuseful, for example, in planning an intensity modulated radiationtherapy session for treatment of a lung cancer. FIG. 3 shows a coronalview of the spinal column. It will be seen that the “S”-shaped spine Slies substantially within a coronal plane P_(cor). Accordingly, the useradvantageously selects the coronal plane P_(cor) as one of thecontouring planes 82 using the contouring plane selector 70 operating inconjunction with the user interface 32. Additionally, to adequatelydelineate the spine S in three-dimensional space, a second contouringplane is advantageously selected. An illustrated oblique plane P_(obl)is suitably selected as a second contouring plane 82 that is differentfrom and non-parallel with the coronal contouring plane P_(cor). (Notethat the oblique contouring plane P_(obl) is viewed “edge-on” and henceappears as a line in FIG. 3). In general, it is sometimes advantageousto select two different, non-parallel contouring planes that areoriented substantially orthogonal to one another, as is the case for theillustrated example contouring planes P_(cor) and P_(obl). FIG. 4 showscoronal plane contours C_(cor) drawn in the coronal contouring planeP_(cor). FIG. 5 shows oblique plane contours C_(obl) drawn in theoblique contouring plane P_(obl). FIG. 6 shows a perspective view of aportion of an example mesh M_(S) constructed by the three-dimensionalmesh generator 74 to delineate the spine S. The mesh M_(S) includesconstrained vertices V_(C) that are constrained to lie on or near thecontours C_(obl), C_(cor). The illustrated three-dimensional polygonalmesh M_(S) employs triangular elements; however, a mesh of otherpolygonal elements such as quadrilateral elements can also be used.

With reference to FIG. 7, a suitable embodiment of the three-dimensionalmesh optimizer 76 is illustrated. The mesh optimizer 76 uses an energyor force minimization algorithm. A constrained vertices identifier 100identifies constrained vertices 102 as those vertices of thethree-dimensional polygonal mesh 90 that are closest to the contours 84.That is, the constrained vertices 102 are identified based on minimumvertex distance from the contours 84. In some embodiments, theconstrained vertices 102 are identified using a Euclidean distancetransform.

In some embodiments, each of the constrained vertices 102 is moved ontothe nearest contour, for example by projecting the vertex onto thecontour. The constrained vertices 102 are then held in fixed positionduring the deformation of the mesh 90. In other embodiments, constraintenergy or force terms 104 are computed based on the minimum distancebetween each constrained vertex and its nearest contour, and the energyor force minimization deformation process incorporates the constraintenergy or force terms 104 into the minimization process.

A deformation processor 110 minimizes the energy or force terms. Theseterms may include, for example, the constraint energy or force terms104, contrast-based energy or force terms 112 derived from contrastdelineating at least a portion of the structure of interest in thethree-dimensional image or map 80, and/or deformation energy or forceterms 114 derived from an extent of deformation of the three-dimensionalpolygonal mesh 90 from the default mesh configuration 92. The optionalcontrast-based energy or force terms 112 incorporate the image contrastfor the structure of interest into the mesh deformation process, whilethe optional deformation energy or force terms 114 account for anexpectation that the mesh 90 should not deviate too far from theexpected, i.e., default mesh configuration 92. By making the optionalconstraint energy or force terms dominant (e.g., large) the deformationis strongly biased toward placing each constrained vertex on or near theproximate contour. In other embodiments, each constrained vertex isprojected onto the proximate contour, and is not moved by thedeformation processor 110.

As another example approach for handling the constrained vertices 102, asmooth initial deformation function is defined based on translating eachconstrained vertex onto the nearest delineating contour. Other verticesin the vicinity of the constrained vertex are moved according to atranslation vector multiplied with a smooth Gaussian function of thegeodesic distance to the constrained vertex. The constrained vertices102 serve as boundary conditions in the deformation process, while theremaining vertex translations are used in computing an external energythat is minimized by the deformation process.

In some embodiments, the three-dimensional polygonal mesh 90 is deformedby the deformation processor 110 based on minimizing an internal energyE=Σ(x_(i)−y_(i))² where x, and y, are mesh vertices connected by asingle edge, subject to boundary conditions (such as having theconstrained vertices at fixed positions on the contours 84) or furtherincluding one or more of the energy or force terms 104, 112, 114 intothe summation that defines the energy figure-of-merit E.

In some embodiments, the deformation process implemented by thedeformation processor 110 is an iterative process, and the constrainedvertices 102 are re-identified by the constrained vertices processor 100during each iteration. In this approach, the sub-set of the vertices ofthe mesh 90 that make up the constrained vertices may change from oneiteration of to the next. In some embodiments, the number of constrainedvertices is fixed. In some embodiments, the number of constrainedvertices is defined respective to the length of the contours 84, underthe assumption that there should be a fixed linear density ofconstrained vertices for each unit length of contour. In otherembodiments, the number of constrained vertices is not fixed, and anyvertex whose minimum distance from the nearest delineation contour 84 isless than a threshold value is identified as a constrained vertex. Othertechniques can also be used.

With returning reference to FIG. 2, the contouring processor 44 can beapplied in various ways. In a substantially manual approach, the userdefines two or more different, non-parallel contours 84 using thecontouring plane and contour selector components 70, 72 along with theuser interface 32. The contours 84 can be curved or straight segments orclosed contours. In some circumstances, a structure of interest can besufficiently delineated by two different non-parallel contours 84, suchas a delineating contour in each of a sagittal plane and a coronalplane. Delineation with only a few contours (possibly as few as twocontours) is enabled by providing the capability to contour in anarbitrary contouring plane such that contours in different, non-parallelplanes can be defined. Effective rapid contouring is further enhanced byselecting the contouring planes as anatomically significant directionsthat contain the structure of interest, such as the illustrated exampleP_(cor) and P_(obl) planes that are anatomically significant respectiveto the example spine S. The mesh 90 is deformed such that the contoursare a sub-set of the mesh surface, while the remainder of the mesh isdeformed according to an internal energy constraint to ensure thetopological integrity of the mesh. Preferably, at least two of thedelineating contours are orthogonal or near orthogonal to each other. Ifthe resulting mesh is not satisfactory, an iterative manual refinementcan be performed in which the user reviews the mesh 90 superimposed onthe image 80 on the display 38, and the existing delineating contoursadjusted or additional delineating contours added so as to furtherconstrain and improve the shape of the mesh 90. In a more automatedapproach, the mesh can be initially deformed to match the image as perFIG. 7, followed by manual defining of contours 84 to correct areaswhere the automatically fitted mesh is not satisfactory. After manuallydefining the contours, further automated adaptation can be done with thecontours acting as hard constraints.

Moreover, the contouring processor 44 can be applied to adjust thecontours for subsequent radiation therapy sessions in an adaptivemanner. For example, planning images for planning a subsequent radiationtherapy session are expected to be similar to the planning images forthe previous radiation therapy session. Differences may include areduced size of the cancerous tumor or growth due to positive effect ofthe radiation therapy, shifting or drift of organs or other structuresover time, or so forth. These minor changes are readily accounted for byuser adjustment of the contouring planes and/or delineating contours,optionally including additional automated optimization. The disclosedcontouring processor 44 can similarly be used to adjust a delineatingmesh between sessions of other types of adaptive treatment processes,for example surgical treatment such as stent implantation.

The invention has been described with reference to the preferredembodiments. Modifications and alterations may occur to others uponreading and understanding the preceding detailed description. It isintended that the invention be constructed as including all suchmodifications and alterations insofar as they come within the scope ofthe appended claims or the equivalents thereof.

Having thus described the preferred embodiments, the invention is nowclaimed to be:
 1. A method of delineating a structure of interest in athree-dimensional image or map, the method comprising: acquiring thethree-dimensional image or map; manually selecting at least twodifferent contouring planes in the three-dimensional image or map thatare different and non-parallel respective to each other; manuallydefining at least two contours delineating the structure of interest,the at least two manually defined contours lying in the at least twodifferent contouring planes that are different and non-parallelrespective to each other; identifying a sub-set of vertices of athree-dimensional polygonal mesh as constrained vertices based onminimum vertex distance from the at least two manually defined contours;projecting each constrained vertex onto the nearest manually definedcontour of the at least two manually defined contours wherein theprojecting does not use an iterative mesh deformation process operatingon the three-dimensional polygonal mesh; and after projecting theconstrained vertices of the three-dimensional polygonal mesh onto themanually defined contours, automatically fitting the three-dimensionalpolygonal mesh to the structure of interest in the three-dimensionalimage or map using an iterative mesh deformation process while, duringthe iterative mesh deformation process, holding the constrained verticesof the three-dimensional polygonal mesh in their respective projectedpositions on the manually defined contours.
 2. The method as set forthin claim 1, further comprising: prior to the identifying operation,initializing the three-dimensional polygonal mesh to a default meshconfiguration located at the center of a bounding box containing the atleast two manually defined contours.
 3. The method as set forth in claim1, further comprising: prior to the identifying operation, initializingthe three-dimensional polygonal mesh to a default mesh configurationlocated at a center-of-gravity of the at least two manually definedcontours.
 4. The method as set forth in claim 1, wherein the minimumdistance used for identifying the constrained vertices is defined by aEuclidean distance transform.
 5. The method as set forth in claim 1,wherein the manual defining comprises: manually selecting the at leasttwo different contouring planes from the group of planes consisting ofsagittal, coronal, and axial planes.
 6. The method as set forth in claim1, wherein the manual defining comprises: manually selecting the atleast two different contouring planes including at least one obliqueplane not belonging to the group of planes consisting of sagittal,coronal, and axial planes.
 7. The method as set forth in claim 1,wherein the acquiring comprises: acquiring a stack of axial image slicesdefining the three-dimensional image or map.
 8. A method of delineatinga structure of interest in a three-dimensional image or map, the methodcomprising: acquiring the three-dimensional image or map; manuallyselecting at least two different contouring planes in thethree-dimensional image or map that are different and non-parallelrespective to each other; manually defining at least two contoursdelineating the structure of interest, the at least two manually definedcontours lying in the at least two different contouring planes that aredifferent and non-parallel respective to each other; identifying asub-set of vertices of a three-dimensional polygonal mesh as constrainedvertices based on minimum vertex distance from the at least two manuallydefined contours; positioning each constrained vertex on the nearestmanually defined contour of the at least two manually defined contourswherein the positioning does not use a mesh deformation processoperating on the three-dimensional polygonal mesh, the positioningoperation further including moving vertices of the three-dimensionalpolygonal mesh that are near a constrained vertex according to atranslation vector multiplied with a Gaussian function of the geodesicdistance to the constrained vertex; and after positioning theconstrained vertices of the three-dimensional polygonal mesh on themanually defined contours, automatically fitting the three-dimensionalpolygonal mesh to the structure of interest in the three-dimensionalimage or map using a mesh deformation process while holding theconstrained vertices of the three-dimensional polygonal mesh in fixedpositions on the manually defined contours.
 9. An apparatus comprising:a computed tomography (CT) scanner configured to acquire a stack ofaxial image slices; a user interface including a display device and atleast one user input device configured to provide: a plane selectioninterface configured to manually select a contouring plane of selectableorientation in a three-dimensional image or map defined by the stack ofaxial image slices; and a contouring interface configured to enable auser to manually define a contour in the selected contour plane; and amesh constructor comprising a processor configured to construct athree-dimensional polygonal mesh delineating a structure of interest inthe three-dimensional image or map, the mesh constructor identifying asub-set of vertices of the three-dimensional polygonal mesh asconstrained vertices and projecting the constrained vertices onto aplurality of non-coplanar delineation contours manually defined usingthe contouring interface and then, after projecting the constrainedvertices onto the plurality of non-coplanar delineation contours,deforming the polygonal mesh to minimize energy or force terms of thevertices of the three-dimensional polygonal mesh other than theconstrained vertices while holding the constrained vertices in theirrespective projected positions on the contours during the deforming. 10.The apparatus as set forth in claim 9, wherein the at least one userinput device of the user interface includes a pointing device.
 11. Theapparatus as set forth in claim 9, further including: a planningprocessor configured to plan a radiotherapy session based on thethree-dimensional image or map and the constructed three-dimensionalpolygonal mesh delineating the structure of interest in thethree-dimensional image or map.
 12. The apparatus as set forth in claim9, wherein the plane selection interface is configured to enable manualselecting of an axial, sagittal, or coronal contouring plane, and thecontouring interface is configured to enable manual defining of acontour in said axial, sagittal, or coronal contouring plane.
 13. Theapparatus as set forth in claim 12, wherein the plane selectioninterface is further configured to enable manual selecting of an obliquecontouring plane that is not an axial, sagittal, or coronal plane, andthe contouring interface is configured to enable manual defining of acontour in said oblique contouring plane.
 14. An apparatus operative inconjunction with an adaptive treatment process, the apparatuscomprising: a segmenting processor configured to delineate a structurein a three-dimensional image or map defined by a stack oftwo-dimensional image slices, the segmenting processor including: acontouring user interface, including a display device and at least oneuser input device, via which a user manually selects at least twodifferent, non-parallel contouring planes in the three-dimensional imageor map and defines structure-delineating contours in the at least twodifferent, non-parallel contouring planes, and a mesh constructorcomprising a processor configured to construct a three-dimensionalpolygonal mesh using a mesh deformation process constrained at least bythe at least two different, non-parallel manually definedstructure-delineating contours wherein the mesh constructor isconfigured to construct the three-dimensional polygonal mesh byoperations including (i) identifying a sub-set of vertices of thethree-dimensional polygonal mesh closest to the at least two different,non-parallel manually defined structure-delineating contours ascontained vertices, (ii) positioning the constrained vertices on the atleast two different, non-parallel manually defined structure-delineatingcontours, and (iii) performing the mesh deformation process whileholding the constrained vertices in fixed position on the at least twodifferent, non-parallel manually defined structure-delineating contours.15. The apparatus as set forth in claim 14, further comprising: aplanning processor configured to identify parameters for adaptivetreatment of a subject based on delineation via the segmenting processorof at least one structure of interest in a three-dimensional image ormap of the subject.
 16. The apparatus as set forth in claim 15, whereinthe planning processor includes: an inverse planning processor fordetermining beamlet parameters for delivering a selected radiationprofile to the subject; and a conversion processor for converting thebeamlet parameters into control parameters for an intensity modulatedradiotherapy system.
 17. The apparatus as set forth in claim 16, furtherincluding: said intensity modulated radiotherapy system configured todeliver radiation to the subject in accordance with said controlparameters.